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检索条件"任意字段=16th ACM Symposium on Principles and Practice of Parallel Programming"

共 407 条记录，以下是141-150 订阅

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Structure-driven Optimizations for Amorphous Data-parallel Programs

Structure-driven Optimizations for Amorphous Data-parallel P...

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15th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Mendez-Lojo, Mario Nguyen, Donald Prountzos, Dimitrios Sui, Xin Hassaan, M. Amber Kulkarni, Milind Burtscher, Martin Pingali, Keshav Univ Texas Austin Inst Computat Engn & Sci Austin TX 78712 USA

ISBN: (纸本)9781605587080

Irregular algorithms are organized around pointer-based data structures such as graphs and trees, and they are ubiquitous in applications. Recent work by the Galois project has provided a systematic approach for parallelizing irregular applications based on the idea of optimistic or speculative execution of programs. However, the overhead of optimistic parallel execution can be substantial. In this paper, we show that many irregular algorithms have structure that can be exploited and present three key optimizations that take advantage of algorithmic structure to reduce speculative overheads. We describe the implementation of these optimizations in the Galois system and present experimental results to demonstrate their benefits. To the best of our knowledge, this is the first system to exploit algorithmic structure to optimize the execution of irregular programs.

关键词： Amorphous Data-parallelism Irregular Programs Optimistic parallelization Synchronization Overheads Cautious Operator Implementations One-shot Optimization Iteration Coalescing

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Initial study of multi-endpoint runtime for MPI+OpenMP hybrid programming model on multi-core systems 14

Initial study of multi-endpoint runtime for MPI+OpenMP hybri...

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2014 19th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

作者： Luo, Miao Lu, Xiaoyi Hamidouche, Khaled Kandalla, Krishna Panda, Dhabaleswar K. Dept. of Computer Science and Engineering Ohio State University United States

ISBN: (纸本)9781450326568

State-of-the-art MPI libraries rely on locks to guarantee thread-safety. this discourages application developers from using multiple threads to perform MPI operations. In this paper, we propose a high performance, lock-free multiendpoint MPI runtime, which can achieve up to 40% improvement for point-to-point operation and one representative collective operation with minimum or no modifications to the existing applications.

关键词： Locks (fasteners)

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parallel programming with big operators 13

Parallel programming with big operators

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18th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2013

作者： Park, Changhee Steele Jr., Guy L. Tristan, Jean-Baptiste KAIST Seoul Korea Republic of Oracle Labs. Burlington MA United States

ISBN: (纸本)9781450319225

In the sciences, it is common to use the so-called "big operator" notation to express the iteration of a binary operator (the reducer) over a collection of values. Such a notation typically assumes that the reducer is associative and abstracts the iteration process. Consequently, from a programming point-of-view, we can organize the reducer operations to minimize the depth of the overall reduction, allowing a potentially parallel evaluation of a big operator expression. We believe that the big operator notation is indeed an effective construct to express parallel computations in the Generate/Map/Reduce programming model, and our goal is to introduce it in programming languages to support parallel programming. the effective definition of such a big operator expression requires a simple way to generate elements, and a simple way to declare algebraic properties of the reducer (such as its identity, or its commutativity). In this poster, we want to present an extension of Scala with support for big operator expressions. We show how big operator expressions are defined and how the API is organized to support the simple definition of reducers with their algebraic properties. © 2013 Authors.

关键词： parallel programming

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parallel Block-Delayed Sequences 22

Parallel Block-Delayed Sequences

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27th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Westrick, Sam Rainey, Mike Anderson, Daniel Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450392044

programming languages using functions on collections of values, such as map, reduce, scan and filter, have been used for over fifty years. Such collections have proven to be particularly useful in the context of parallelism because such functions are naturally parallel. However, if implemented naively they lead to the generation of temporary intermediate collections that can significantly increase memory usage and runtime. To avoid this pitfall, many approaches use "fusion" to combine operations and avoid temporary results. However, most of these approaches involve significant changes to a compiler and are limited to a small set of functions, such as maps and reduces. In this paper we present a library-based approach that fuses widely used operations such as scans, filters, and flattens. In conjunction with existing techniques, this covers most of the common operations on collections. Our approach is based on a novel technique which parallelizes over blocks, with streams within each block. We demonstrate the approach by implementing libraries targeting multicore parallelism in two languages: parallel ML and C++, which have very different semantics and compilers. To help users understand when to use the approach, we define a cost semantics that indicates when fusion occurs and how it reduces memory allocations. We present experimental results for a dozen benchmarks that demonstrate significant reductions in both time and space. In most cases the approach generates code that is near optimal for the machines it is running on.

关键词： parallel programming fusion collections functional programming

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Using GPU's to Accelerate Stencil-based Computation Kernels for the Development of Large Scale Scientific Applications on Heterogeneous Systems 12

Using GPU's to Accelerate Stencil-based Computation Kernels ...

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17th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Tao, Jian Blazewicz, Marek Brandt, Steven R. Louisiana State Univ Ctr Computat & Technol Baton Rouge LA 70803 USA Poznan Supercomp & Networking Ctr Applicat Dept Poznan Poland

ISBN: (纸本)9781450311601

We present CaCUDA - a GPGPU kernel abstraction and a parallel programming framework for developing highly efficient large scale scientific applications using stencil computations on hybrid CPU/GPU architectures. CaCUDA is built upon the Cactus computational toolkit, an open source problem solving environment designed for scientists and engineers. Due to the flexibility and extensibility of the Cactus toolkit, the addition of a GPGPU programming framework required no changes to the Cactus infrastructure, guaranteeing that existing features and modules will continue to work without modification. CaCUDA was tested and benchmarked using a 3D CFD code based on a finite difference discretization of Navier-Stokes equations.

关键词： Algorithms Design Languages GPGPU programming Computational Framework HPC Stencil Computation

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Using Sample-Based Time Series Data for Automated Diagnosis of Scalability Losses in parallel Programs 20

Using Sample-Based Time Series Data for Automated Diagnosis ...

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25th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Wei, Lai Mellor-Crummey, John Rice Univ Dept Comp Sci Houston TX 77005 USA Rice Univ Houston TX USA Pony Ai Fremont CA USA

ISBN: (纸本)9781450368186

the performance of many parallel applications has failed to scale as fast as successive generations of hardware on which these applications execute. To understand the cause of scalability losses, experts use performance tools to monitor and analyze application behavior. Profiles generated by performance tools can usually indicate the presence of scalability losses while time series data are generally necessary to pinpoint the root causes of such losses. However, manual analysis of time series data can be difficult in executions with a large number of processes, long running times, and deep call chains. this paper describes an automated framework that analyzes sample-based time series data to diagnose scalability losses in parallel executions. the framework's automated diagnosis of scalability losses indicates their symptoms, severity, and causes. Two case studies illustrate the effectiveness of this framework. When compared to a tool that analyzes performance using instrumentation-based traces, our overhead for collecting sample-based time series is 1/28 in time and 1/1600 in space while our automated analysis takes 1/25 of the time.

关键词： Performance automated diagnosis scalability losses sample-based time series data

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Extracting logical structure and identifying stragglers in parallel execution traces 14

Extracting logical structure and identifying stragglers in p...

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2014 19th acm SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

作者： Isaacs, Katherine E. Gamblin, Todd Bhatele, Abhinav Bremer, Peer-Timo Schulz, Martin Hamann, Bernd Department of Computer Science University of California Davis United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States

ISBN: (纸本)9781450326568

We introduce a new approach to automatically extract an idealized logical structure from a parallel execution trace. We use this structure to define intuitive metrics such as the lateness of a process involved in a parallel execution. By analyzing and illustrating traces in terms of logical steps, we leverage a developer's understanding of the happened-before relations in a parallel program. this technique can uncover dependency chains, elucidate communication patterns, and highlight sources and propagation of delays, all of which may be obscured in a traditional trace visualization.

关键词： Visualization

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On the fly MHP Analysis 20

On the fly MHP Analysis

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25th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Saha, Sonali Nandivada, V. Krishna IIT Madras Madras Tamil Nadu India

ISBN: (纸本)9781450368186

May-Happen-in-parallel (MHP) analysis forms the basis for many problems of program analysis and program understanding. MHP analysis can also be used by IDEs (integrateddevelopment-environments) to help programmers to refactor parallel-programs, identify racy programs, understand which parts of the program run in parallel, and so on. Since the code keeps changing in the IDE, re-computing the MHP information after every change can be an expensive affair. In this manuscript, we propose a novel scheme to perform incremental MHP analysis (on the fly) of programs written in task parallel languages like X10 to keep the MHP information up to date, in an IDE environment. the key insight of our proposed approach to maintain the MHP information up to date is that we need not rebuild (from scratch) every data structure related to MHP information, after each modification (addition or deletion of statements) in the source code. the idea is to reuse the old MHP information as much as possible and incrementally recompute the MHP information (of a small set of statements) which depends on the statement added/removed. We introduce two new algorithms that deal with addition and removal of parallel constructs like finish, async, atomic, and sequential constructs like loop, if, if-else and other sequential statements, on the fly. Our evaluation shows that our algorithms run much faster than the repeated invocations of the fastest known MHP analysis for X10 programs [Sankar et al. 2016].

关键词： Concurrent programs may happen in parallel analysis incremental analysis

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No Barrier in the Road: A Comprehensive Study and Optimization of ARM Barriers 20

No Barrier in the Road: A Comprehensive Study and Optimizati...

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25th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Liu, Nian Zang, Binyu Chen, Haibo Shanghai Jiao Tong Univ Inst Parallel & Distributed Syst Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Scalable Comp & Syst Shanghai Peoples R China

ISBN: (纸本)9781450368186

In this paper, we present the first comprehensive performance characterization and optimization of ARM barriers on both mobile and server platforms. We draw a set of observations through several abstracted models and validate them in scenarios where barriers are intensively used. We find that (1) order-preserving approaches without involving the bus significantly outperform other approaches, and (2) the tremendous overhead mostly comes from barriers strictly following remote memory references. Usually, such barriers are inserted when threads are exchanging data, and they are used to ensure the relative order between storing the data to a shared buffer and setting a flag to inform the receiver. Based on the observations, we propose a new mechanism, Pilot, to remove such barriers by leveraging the single-copy atomicity to piggyback the flag with the data. Applying Pilot only requires minor changes to applications and provides 10%-360% performance improvements in multiple benchmarks, which are close to the ideal performance without barriers.

关键词： barrier synchronization concurrency lock

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throughput-Oriented GPU Memory Allocation 19

Throughput-Oriented GPU Memory Allocation

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24th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Gelado, Isaac Garland, Michael NVIDIA Santa Clara CA 95051 USA

ISBN: (纸本)9781450362252

throughput-oriented architectures, such as GPUs, can sustain three orders of magnitude more concurrent threads than multicore architectures. this level of concurrency pushes typical synchronization primitives (e.g., mutexes) over their scalability limits, creating significant performance bottlenecks in modules, such as memory allocators, that use them. In this paper, we develop concurrent programming techniques and synchronization primitives, in support of a dynamic memory allocator, that are efficient for use with very high levels of concurrency. We formulate resource allocation as a two-stage process, that decouples accounting for the number of available resources from the tracking of the available resources themselves. To facilitate the accounting stage, we introduce a novel bulk semaphore abstraction that extends traditional semaphore semantics by optimizing for the case where threads operate on the semaphore simultaneously. We also similarly design new collective synchronization primitives that enable groups of cooperating threads to enter critical sections together. Finally, we show that delegation of deferred reclamation to threads already blocked greatly improves efficiency. Using all these techniques, our throughput-oriented memory allocator delivers both high allocation rates and low memory fragmentation on modern GPUs. Our experiments demonstrate that it achieves allocation rates that are on average 16.56 times higher than the counterpart implementation in the CUDA 9 toolkit.

关键词： Concurrency Memory Allocation GPU programming

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